Additive Manufacturing Capabilities Research Articles

Study on machinability of additively manufactured and conventional titanium alloys in micro-milling process

Capability of Additive Manufacturing (AM) technology in the production of complex parts with high flexibility has led to the growing interest in their application as an alternative for conventional manufacturing processes. Despite the outstanding benefits of the AM process, due to their poor surface quality, the precision parts produced by this method generally need to be machined, ground, or polished. This paper addresses the machinability of AM Ti6Al4V titanium alloy parts in the micro-milling process with a specific focus on cutting forces, specific cutting energy, burr formation, and surface quality. Additive parts were produced by Electron Beam Melting (EBM) technique and were compared with the extruded Ti6Al4V parts in the micro-milling process. No significant difference could be observed in the cutting forces of both materials at chip thicknesses between 7.4 and 37.3 μm, despite the higher hardness of the EBM Ti6Al4V compared to the extruded Ti6Al4V. However, micro-milling of the EBM parts produced finer surfaces. Cutting forces and specific cutting energies of EBM parts were less than those of extruded parts at minimal chip thicknesses (lower than 7.4 μm). Continuous wavy-type burrs were formed in micro-milling of the EBM Ti6Al4V and were larger than those of extruded Ti6Al4V.

Incorporating Steric Hindrance into the Additive Design Enables a Robust Formulation of Alumina Ink for Extrusion-based 3D Printing

The capabilities of additive manufacturing for fabrication of complex and thin-walled ceramic-based objects are restricted by the availability of ceramics inks. Formulations of current ink systems ...

A Design Framework for Additive Manufacturing: Integration of Additive Manufacturing Capabilities in the Early Design Process

Additive manufacturing has emerged as an integral part of modern manufacturing because of its unique capabilities in various application domains. As efforts to effectively apply additive manufacturing, design for additive manufacturing (DfAM) has risen to provide a set of guidelines based on a practical design framework or a methodology during the product design process of additive manufacturing. However, most existing DfAM methods do not effectively consider the capabilities of extant additive manufacturing technologies in the early design stages, and therefore it is hard to map functional requirements from customer needs onto a product design for additive manufacturing. Moreover, available DfAM methods tend to rely on the direct application of a specific decision method rather than a systematic approach with appropriate deployment and transformation of available design decision methods considering the additive manufacturing environment. Consequently, existing DfAM methods lack suitability for use by additive manufacturing novices. To tackle these issues, this study develops a design framework for additive manufacturing through the integration of axiomatic design and theory of inventive problem-solving (TRIZ). This integrated approach is effective because the axiomatic design approach can be used to systematically define and analyze a design problem, while the TRIZ problem-solving approach combined with an additive manufacturing database can be used as an idea generation tool to generate innovative solutions for the design problem. A case study for a housing cover redesign is presented to apply and validate the proposed design framework.

Obfuscation of Embedded Codes in Additive Manufactured Components for Product Authentication.

Enhancement in the capabilities of additive manufacturing (AM) methods has led to development of many high-value components for aerospace, automotive and medical fields. Security concerns, such as (a) a predominantly cloud based process chain of AM may be breached and stolen files can be used for unauthorized reproduction of parts and (b) legitimately acquired parts can be reverse engineered, need to be addressed for this field to protect intellectual property and deter counterfeiting or unauthorized production. In the present work, a method of embedding an identification code inside the parts manufactured by AM methods is presented, which takes advantage of the layer-by-layer manufacturing process. The code is obfuscated by segmenting it into a specific number of parts, which are distributed throughout a large number of printed layers. In this case, viewing the code only from a specific direction is provides the correct visualization. A further obfuscation scheme is demonstrated that embeds multiple identification codes in the interpenetrating format. Only a specific set of processing conditions can lead to printing of the authentic code inside the part correctly. Numerous other conditions lead to printing of wrong code inside the part, which will lead to positive identification of counterfeit or unauthorized parts. Securing the AM process chain can help in accelerating the industrial applications of this versatile method.

Exploratory study on the perception of additively manufactured end-use products with specific questionnaires and eye-tracking

The outreach of application domains for Additive Manufacturing (AM) is expanding and end-use products represent their next frontier. Contextually, design methods are developed for exploiting the unique AM capabilities. They largely benefit from the knowledge about peculiarities, constraints and technical performances of the various AM processes and devices. However, while the mechanical properties of objects created with AM are widely studied, there is lack of research on emotional and perceptual aspects. This is of great relevance in the mentioned perspective of employing AM for end-use products. The paper aims to elucidate which perceptual mechanisms are activated when a user observes an object generated with AM instead of traditional technologies. An experiment has involved 43 participants who have evaluated ten pairs of objects, constituted by a commercial product and a replica made with Fused Deposition Modelling. Testers have answered a questionnaire, as well as their visual behavior has been recorded with eye-tracking glasses. Based on results, replicas suffer from poor attractiveness and especially low perceived quality. They have also given rise to more careful exploratory behaviors because they likely require a lengthier examination for testers’ assessment or they arouse curiosity. It can be inferred that Fused Deposition Modelling does not exhibit sufficient accuracy to achieve acceptability with reference to everyday products. Nevertheless, it is also deemed that limited improvements might compensate for the perception of technical unsuitability this technology engenders. This can be verified by repeating the experiment with more sophisticated and precise AM devices.

Selective Laser Melting of a 1U CubeSat structure. Design for Additive Manufacturing and assembly

The aerospace industry has used Additive Manufacturing (AM) since its beginnings in the ‘80s because of its unique capabilities. The present work shows a re-designing and the manufacturing via AM of the structural sub-system of a CubeSat from the nanosatellite class. Specifically, a 1U CubeSat design proposal has been developed according to Design for Additive Manufacturing (DFAM) guidelines, considering the consolidation of the parts for reducing and/or avoiding the assembly issues. A configuration made of only two parts has been successfully fabricated via Selective Laser Melting (SLM) technology. AM capabilities allowed to integrate a hinge mechanism in the design, making the resulting structure an already-assembled one. Moreover, the design exhibits snap-fit features in order to get rid of fasteners. The increased complexity of the parts due to the integration of the additional snap-fit features results in no manufacturing issues due to the AM capability to manage shape complexity. This work points AM out as a key technology allowing for a drastic reduction of the part count for a mechanical system, taking Design for Assembly (DFA) guidelines to the extreme. It underlines the need to consider AM-related constrains already in the design phase, such as the clearance and the shape of the hinge and the snap joint matching SLM specific constraints such as support structures design and removal planning, part orientation in the building platform, and hollowing out for powder removal.

Why manufacturers adopt additive manufacturing technologies: The role of sustainability

Emerging manufacturing technologies can affect the performance of manufacturing systems considerably. Hence, a proportionate and purposive choice of such technologies would significantly impact the success of a firm. Additive Manufacturing, a leading and impactful technology, is being implemented in many industrial sectors and for a variety of reasons. It presents huge potential benefits in terms of sustainability perspectives. This paper aims to identify and prioritize the determinants of its adoption as well as to clarify the role of sustainability benefits in the decision to adopt. Then, the research seeks to distinguish the priorities of different application sectors through a multi-stage survey. The results show that environmental sustainability benefits are barely relevant to adoption decisions in practice and this is in contrast with the literature stating the huge sustainability benefits. Moreover, the results prove the pivotal role of economic motives in adoption decisions. The findings also indicate that the capability of additive manufacturing for producing almost any complex design is the key driver of its adoption in all sectors.

Optimizing Topology and Gradient Orthotropic Material Properties Under Multiple Loads

The goal of this research is to optimize an object's macroscopic topology and localized gradient material properties (GMPs) subject to multiple loading conditions simultaneously. The gradient material of each macroscopic cell is modeled as an orthotropic material where the elastic moduli in two local orthogonal directions we call x and y can change. Furthermore, the direction of the local coordinate system can be rotated to align with the loading conditions on each cell. This orthotropic material is similar to a fiber-reinforced material where the number of fibers in the local x and y-directions can change for each cell, and the directions can as well be rotated. Repeating cellular unit cells, which form a mesostructure, can also achieve these customized orthotropic material properties. Homogenization theory allows calculating the macroscopic averaged bulk properties of these cellular materials. By combining topology optimization with gradient material optimization and fiber orientation optimization, the proposed algorithm significantly decreases the objective, which is to minimize the strain energy of the object subject to multiple loading conditions. Additive manufacturing (AM) techniques enable the fabrication of these designs by selectively placing reinforcing fibers or by printing different mesostructures in each region of the design. This work shows a comparison of simple topology optimization, topology optimization with isotropic gradient materials, and topology optimization with orthotropic gradient materials. Finally, a trade-off experiment shows how different optimization parameters, which affect the range of gradient materials used in the design, have an impact on the final objective value of the design. The algorithm presented in this paper offers new insight into how to best take advantage of new AM capabilities to print objects with gradient customizable material properties.

Novel 3D Printed Modular Hemipelvic Prosthesis for Successful Hemipelvic Arthroplasty: A Case Study

In this study, in order to prevent the failure of hemipelvic arthroplasty using a patient-specific Computer-Aided Design (CAD) and Additive Manufacturing (AM) approach, a new design for modular hemipelvic prosthesis was developed. Moreover, the biomechanical properties of the new design were determined. The 3D printed pelvic prosthesis with a sacrum portion that completely matches the back surface of the patient’s sacrum offers more potential for bone ingrowth between the host bone and prosthesis. The new approach integrated the capabilities of digital medical imaging techniques, CAD and metal AM to realize a modular hemipelvic prosthesis. The patient’s pelvic Digital Imaging and Communication in Medicine (DICOM) data were imported into Mimics software to construct a digital representative patient model for design of the prosthesis. A physical model was obtained using a Stereolithography (SLA) 3D printer for preoperative planning. The final customized implant was designed by using UG NX 10.0 software. Then a surgically modular hemipelvic prosthesis was fabricated from the Ti6Al4V titanium alloy by electron beam melting technology. The operation was performed according to the preoperative planning. The outcome of the operation was good at the 6-month follow-up. Also, the stress distribution and the relative micromotion revealed positive results based on a finite element model built to detect prosthesis stability. The 3D printed modular hemipelvic prosthesis provided good resolution for the failure of hemipelvic arthroplasty. Personal customization will be important in future surgeries aiming at improving the anatomy and function of the implant.

Bi-material strip based temperature sensor design and optimization through thermo-mechanical multi-physics modeling

ABSTRACTWith the capability of additive manufacturing, complex structures are easily fabricated to achieve various design purposes. In this work, a bi-material strip temperature sensor with complex periodic pattern design is purposed and investigated through both the analytical modeling and multi-physics finite element analysis. Three design patterns are considered: standard, E-shape and S-shape. In the standard solid strip design, the curvature of the bi-material strip under temperature variation is in a linear relationship with the coefficient of thermal expansion (CTE) difference, but in a reciprocal relationship with the strip thickness. The curvature of the bi-material strip depends on the Young’s modulus ratio and layer thickness ratio of the two materials, but is independent of the magnitude of the materials’ Young’s modulus. Based on analytical derivation and numerical validation, the optimized design parameters can be provided. Compared to S-shape pattern design, E-shape pattern design can significantly increase the temperature sensitivity of the bi-material strip. An analytical prediction of the E-shape pattern’s temperature sensitivity is introduced and discussed. This work proves the concept that new design space becomes available with the capability of additive manufacturing, and provides the general design guideline for a bi-material strip based temperature sensor with possible design patterns.

Evaluating the Readiness Level of Additively Manufactured Digital Spare Parts: An Industrial Perspective

Additive manufacturing of digital spare parts offers promising new possibilities for companies to drastically shorten lead times and to omit storage costs. However, the concept of digital spare parts has not yet gained much footing in the manufacturing industry. This study aims to identify grounds for its selective rejection. Conducted from a corporate perspective, outlining a holistic supply chain network structure to visualize different digital spare part distribution scenarios, this survey study evaluates technical and economic additive manufacturing capabilities. Results are analyzed and discussed further by applying the Mann-Whitney test to examine the influence of the company size and the presence of 3D-printed end-use components within supply networks on gathered data. Machines’ limited build chamber volumes and the necessity of post-processing are considered as the main technical challenges of current additive manufacturing processes. Furthermore, it can be concluded that company sizes have a significant effect on perceived technological limitations. Overall, the results lead to the conclusion that the readiness level of the digital spare parts concept demands for further development.

A numerical-based part consolidation candidate detection approach with modularization considerations

Aided by the capabilities of additive manufacturing in building a part with multiple materials, dynamic sub-components, and complex geometries, the number of parts that are feasible for consolidation has increased drastically. However, to decide which components to consolidate is difficult. Therefore, to identify these potential candidates out of a complex product is highly demanded. We define this issue as a part consolidation candidate detection (PCCD) problem. To solve this problem, we proposed three principles that rationalize the PCCD process with regard to the maximum number and the priority of parts to be consolidated. Based on which, we developed a modularity-based PCCD (MPCCD) framework which is featured by the need for module division and community detection as well as two PCCD algorithms [i.e., strength-based numerical PCCD (NPCCD) and community-based PCCD (CPCCD)]. Two case studies of a throttle pedal and an octocopter are given to demonstrate the effectiveness of the proposed CPCCD algorithm and the MPCCD framework, respectively. In the end, this paper is wrapped up with important conclusions and future research.

Considerations on 3D printing joints parts

One of the unique capabilities of additive manufacturing over classical manufacturing methods is the possibility to create interlocking parts without the need of assembly. This is useful for the creation of rotational and translational joints in demonstrative or functional 3D models. This paper focuses on analyzing the process parameters which need to be considered when fabricating parts with cylindrical or spherical rotating joints using material extrusion 3D printing. Several aspects are analyzed, such as joint tolerance and clearance, surface finish requirements, surface shape and dimensions or surface precision and trueness as they result from the converting ideal CAD files to the common file formats used in additive manufacturing. The paper also searches to identify the extent to which it is possible to dynamically change process parameters such as layer height and width or depositing speed in order to improve the characteristics of the inner and outer surfaces of the joints, without influencing other areas of the fabricated parts.

A Novel Design Method for Nonuniform Lattice Structures Based on Topology Optimization

Lattice structures are broadly used in lightweight structure designs and multifunctional applications. Especially, with the unprecedented capabilities of additive manufacturing (AM) technologies and computational optimization methods, design of nonuniform lattice structures has recently attracted great research interests. To eliminate constraints of the common “ground structure approaches” (GSAs), a novel topology optimization-based method is proposed in this paper. Particularly, the structural wall thickness in the proposed design method was set as uniform for better manufacturability. As a solution to carry out the optimized material distribution for the lattice structure, geometrical size of each unit cell was set as design variable. The relative density model, which can be obtained from the solid isotropic microstructure with penalization (SIMP)-based topology optimization method, was mapped into a nonuniform lattice structure with different size cells. Finite element analysis (FEA)-based homogenization method was applied to obtain the mechanical properties of these different size gradient unit cells. With similar mechanical properties, elements with different “relative density” were translated into unit cells with different size. Consequently, the common topology optimization result can be mapped into a nonuniform lattice structure. This proposed method was computationally and experimentally validated by two different load-support design cases. Taking advantage of the changeable surface-to-volume ratio through manipulating the cell size, this method was also applied to design a heat sink with optimum heat dissipation efficiency. Most importantly, this design method provides a new perspective to design nonuniform lattice structures with enhanced functionality and manufacturability.

Surface roughness evaluation of additive manufactured metallic components from white light images captured using a flexible fiberscope

The added capabilities of Additive Manufacturing (AM) while processing metallic components have revolutionized the design and manufacturing flexibility of multitudes of aerospace components. However, AM being a stochastic process results in a degraded control of the surface topography of the printed structure and thus requires adequate finishing processes before implementation. Particularly, in the case of components having complex cross-sections and internal channels, none of the currently available technologies offer a solution for the measurement and certification of surface roughness parameters. In this context, this paper investigates a binary image processing technique applied to multiple white light images captured by a 0.3 mm diameter micro fiber endoscope. Further, AM sample surfaces generated by different build angles are investigated to demonstrate the advantages of the proposed technique. A surface roughness evaluation parameter is presented along with measurement results obtained using the Mitutoyo SJ400 (conventional profiler) and the Talyscan 150 (optical profiler).

Automated process planning for hybrid manufacturing

Hybrid manufacturing (HM) technologies combine additive and subtractive manufacturing (AM/SM) capabilities, leveraging AM’s strengths in fabricating complex geometries and SM’s precision and quality to produce finished parts. We present a systematic approach to automated computer-aided process planning (CAPP) for HM that can identify non-trivial, qualitatively distinct, and cost-optimal combinations of AM/SM modalities. A multimodal HM process plan is represented by a finite Boolean expression of AM and SM manufacturing primitives, such that the expression evaluates to an ‘as-manufactured’ artifact. We show that primitives that respect spatial constraints such as accessibility and collision avoidance may be constructed by solving inverse configuration space problems on the ‘as-designed’ artifact and manufacturing instruments. The primitives generate a finite Boolean algebra (FBA) that enumerates the entire search space for planning. The FBA’s canonical intersection terms (i.e., ‘atoms’) provide the complete domain decomposition to reframe manufacturability analysis and process planning into purely symbolic reasoning, once a subcollection of atoms is found to be interchangeable with the design target. We therefore show that geometric and spatial reasoning can be decoupled from logic and combinatorial search required to find process plans. The approach subsumes unimodal (all-AM or all-SM) process planning as special cases. We demonstrate the practical potency of our framework and its computational efficiency when applied to process planning of complex 3D parts with dramatically different AM and SM instruments.

A multi-material part design framework in additive manufacturing

Additive manufacturing (AM) technologies provide more freedom to functional part design in various industries. One of the unique capabilities of AM is that multi-material parts can be produced with material compositional and geometric complexity. Multi-material parts have the advantage of achieving multiple performance requirements. In the research, we propose a framework for designing multi-material parts using AM processes. The proposed framework is composed of four interacting modules, including design requirement identification, primary material selection, AM process selection, material composition, and part geometry determination. Rules and guidelines for AM are integrated into the proposed framework with AM processes’ capabilities and constraints compiled in databases. We also introduce databases to assist in decision-making and ensure manufacturability of the designed multi-material part in various product design phases. The proposed framework is applied to a case study involving a conceptual design of a multi-material battery pack cooling plate.

A Knowledge-Based Method for Innovative Design for Additive Manufacturing Supported by Modular Ontologies

Additive manufacturing (AM) offers significant opportunities for product innovation in many fields provided that designers are able to recognize the potential values of AM in a given product development process. However, this may be challenging for design teams without substantial experience with the technology. Design inspiration based on past successful applications of AM may facilitate application of AM even in relatively inexperienced teams. While designs for additive manufacturing (DFAM) methods have experimented with reuse of past knowledge, they may not be sufficient to fully realize AM's innovative potential. In many instances, relevant knowledge may be hard to find, lack context, or simply unavailable. This design information is also typically divorced from the underlying logic of a products' business case. In this paper, we present a knowledge based method for AM design ideation as well as the development of a suite of modular, highly formal ontologies to capture information about innovative uses of AM. This underlying information model, the innovative capabilities of additive manufacturing (ICAM) ontology, aims to facilitate innovative use of AM by connecting a repository of a business and technical knowledge relating to past AM products with a collection of knowledge bases detailing the capabilities of various AM processes and machines. Two case studies are used to explore how this linked knowledge can be queried in the context of a new design problem to identify highly relevant examples of existing products that leveraged AM capabilities to solve similar design problems.

Quantifying fatigue property changes in material jetted parts due to functionally graded material interface design

The capability of Additive Manufacturing (AM) to manufacture multi-materials allows the fabrication of complex and multifunctional objects with heterogeneous material compositions and varying mechanical properties. The material jetting AM process specifically has the capability to manufacture multi-material structures with both rigid and flexible material properties. Existing research has investigated the fatigue properties of 3D printed multi-material specimens and shows that there is a weakness at multi-material interfaces. This paper seeks to, instead, investigate the effects of gradual material transitions on the fatigue life of 3D printed multi-material specimens. In order to examine the fatigue life at the multi-material interface, stepwise gradients are compared against continuous gradients created through voxel-based design. Results demonstrate the effects of different material gradient patterns and different material transition lengths on the fatigue life of multi-material specimens. In addition, the behavior of individual material composites is studied to confirm how gradient designs based on different material compositions affect their material properties.

Additive Manufacturing-Enabled Part Count Reduction: A Lifecycle Perspective

Part count reduction (PCR) is one of the typical motivations for using additive manufacturing (AM) processes. However, the implications and trade-offs of employing AM for PCR are not well understood. The deficits are mainly reflected in two aspects: (1) lifecycle-effect analysis of PCR is rare and scattered; (2) current PCR rules lack full consideration of AM capabilities and constraints. To fill these gaps, this paper first summarizes the main effect of general PCR (G-PCR) on lifecycle activities to make designers aware of potential benefits and risks and discusses in a point-to-point fashion the new opportunities and challenges presented by AM-enabled PCR (AM-PCR). Second, a new set of design rules and principles are proposed to support potential candidate detection for AM-PCR. Third, a dual-level screening and refinement design framework is presented aiming at finding the optimal combination of AM-PCR candidates. In this framework, the first level down-samples combinatory space based on the proposed new rules while the second one exhausts and refines each feasible solution via design optimization. A case study of a motorcycle steering assembly is considered to demonstrate the effectiveness of the proposed design rules and framework. In the end, possible challenges and limitations of the presented design framework are discussed.